Geli¸stirilen bu yöntem ile gerçek zamanlı olarak frekans tespiti ve frekans de˘gi¸sime ba˘glı olarak modülasyon örüntüsü çıkarılabilmektedir. Bu tez çalı¸smasında ayrıca özgün olarak gerçek zamanlı olarak ultra geni¸sbantta spektrum algılama yapabilen ve çok kanallı ADC yapılarında kullanılabilecek ayarlanabilir FFT modülü FPGA ortamında gerçeklenerek radar sinyal simülatöründe üretilen ara frekans analog LPI radar sinyalleri i¸sleyebilen panoramik sayısal almaç yapısı olu¸sturulmu¸stur. Geli¸stirilen UWB-FFT yapısı farklı FPGA kartlarında gerçeklenebilir oldu˘gundan sayısal teknolojideki de˘gi¸simlerine paralel olarak anlık i¸slenebilecek bant geni¸slikleri arttırılabilecektir.
Yo˘gun ve karma¸sık çoklu i¸saret ortamında panoramik sayısal almaç LPI radar i¸saretlerinin bütüncül olarak analiz edilmesi ve parametrelerinin çıkarılması mümkün olmaktadır. Çoklu ADC kullanımı ile ilgili analizlerden elde edilen sonuçlara göre anlık bant geni¸sliklerinin ADC sayısı kadar arttırılması sa˘glanabilmektedir.
Çoklu i¸saret ortamında alınan LPI radar sinyallerinin öncelikle ayrı¸stırılması sa˘glanmı¸stır. Özgün olarak, ortamda bulunan radar sayısını bilmeden denetimsiz sınıflandırma yöntemleri ile sinyallerin parametrelerine göre DB-SCAN algoritmasını kullanarak kümeleme gerçekle¸stirilmi¸stir ve farklı SNR seviyelerinde kümelerin da˘gılımına yönelik ölçümler gerçekle¸stirilmi¸stir. Ayrı¸stırılan sinyal kümelerinin daha önceden e˘gitilmi¸s CNN yapılarıyla makine ö˘grenmesi tabanlı denetimli sınıflandırma gerçekle¸stirilmi¸stir. Bu tez çalı¸smasında özgün olarak alınan sinyallerin sınıflandırma i¸slemlerini kendi SNR seviyelerinde olu¸sturulmu¸s veri setleriyle e˘gitilmi¸s kaysayılarla gerçele¸stirilmesinin yüksek sınıflandırma do˘grulu˘gunu sa˘gladı˘gı görülmü¸stür. LPI radar sinyallerinden FM ve PM modülasyonların oldu˘gu 19 sınıf bulunan benzetim ortamında LPI radar tespit için iyi bir seviye olan 10 dB SNR’da %93.47 ve normal seviye olan 0 dB SNR’da %88.47 sınıflandırma ba¸sarımı sa˘glanmı¸stır.
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ÖZGEÇM˙I ¸S
Adı Soyadı : Adnan ORDUYILMAZ Do˘gum Yeri : ˙Izmir
Do˘gum Tarihi : 27/08/1981 Medeni Hali : Evli Yabancı Dili : ˙Ingilizce
E˘gitim Durumu
Lise : Bursa A.O.S. Fen Lisesi
Lisans : Bilkent Üniversitesi Mühendislik Fakültesi Elektrik-Elektronik Mühendisli˘gi (1999-2004)
Yüksek Lisans : Mississippi Eyalet Üniversitesi Mühendislik Fakültesi Elektrik Mühendisli˘gi (A˘gustos 2004 - 2006)
Doktora : Ankara Üniversitesi Mühendislik Fakültesi
Elektrik-Elektronik Mühendisli˘gi (A˘gustos 2008 - Mart 2020)
Çalı¸stı˘gı Kurum
Tübitak Bilgem ˙Iltaren - Ba¸suzman Ara¸stırmacı (2006 - Devam Ediyor)
Uluslararası Kongre
Yar, E., Kocamis, M B., Orduyilmaz, A., Serin, M., Efe, M. 2019. A Complete Framework of Radar Pulse Detection and Modulation Classification for Cognitive EW. 27th Europian Signal Processing Conference (EUSIPCO), 2-6 September 2019, Coruna, Spain.
Orduyilmaz, A., Ispir, M., Serin, M., Efe, M. 2019. Ultra Wideband Spectrum Sensing for Cognitive Electronic Warfare Applications. IEEE Radar Conference (RADARCONF), 22-26 April, Boston, USA.
Orduyilmaz, A., Kara, G., Serin, M., Yildirim, A., Gürbüz, A. C., Efe, M. 2015. Real Time Pulse Compression Waveform Generation and Matched Filtering, IEEE